Author:
Yao Jianping,Tran Son N.,Nguyen Hieu,Sawyer Samantha,Longo Rocco
Publisher
Springer Nature Singapore
Reference28 articles.
1. Aich, S., Al-Absi, A.A., Lee Hui, K., Sain, M.: Prediction of quality for different type of wine based on different feature sets using supervised machine learning techniques. In: 2019 21st International Conference on Advanced Communication Technology (ICACT), pp. 1122–1127 (2019)
2. Beaver, C., Collins, T.S., Harbertson, J.: Model optimization for the prediction of red wine phenolic compounds using ultraviolet-visible spectra. Molecules (Basel, Switzerland) 25(7) (2020)
3. Beltrán, N., Duarte-Mermoud, M., Soto Vicencio, V., Salah, S., Bustos, M.: Chilean wine classification using volatile organic compounds data obtained with a fast gc analyzer. IEEE Trans. Instrum. Meas 57(11), 2421–2436 (2008)
4. Blanco, V.Z., Auw, J.M., Sims, C.A., O’Keefe, S.F.: Effect of Processing on Phenolics of Wines, pp. 327–340. Springer, US, Boston, MA (1998). https://doi.org/10.1007/978-1-4899-1925-0_27
5. Castillo-Valero, J.S., Villanueva, E.C., García-Cortijo, M.C.: Regional reputation as the price premium: estimation of a hedonic model for the wines of castile-la mancha. Revista de la Facultad de Ciencias Agrarias 50(2), 293–310 (2018)